1. Field of the Invention
The present invention deals with the correction of distortion in imaging systems, more particularly to systems such as scanners and in cameras used in applications such as image capture and video conferencing.
2. Art Background
With the advent of inexpensive imaging sensors, applications such as video conferencing and remote image capture are becoming more prevalent. As manufacturers provide imaging systems at lower and lower price points, compromises are made especially in the optics provided, leading to systems having geometric lens distortion. As these systems are placed in more locations, problems with illumination arise, both as a result of variations in lighting conditions, as well as the effect of automatic brightness controls in the imaging systems themselves.
The field of motion estimation deals with processing images for example to stitch together successive overlapping images to form a unified mosaic. These motion estimation techniques deal with arrays of pixels, and operate by deriving the motion between a group of pixels in one frame and the same pixels in a new position in a second frame. For motion estimation to succeed, the illumination levels and therefore pixel intensity between the two frames must be the same, and the frames must be relatively free of geometric distortion. What is needed is a way to correct for the effects of geometric lens distortion in motion estimation, and to correct for changes in illumination that effect pixel density.
Motion estimation techniques and the Optical Flow Equation (OFE) are applied to correct for distortion in an imaging system. Geometric lens distortion is corrected using a novel optical correction model. Illumination changes are corrected using both simple and Vignetting models. The solutions involve solving of a set of nonlinear equations. Typical solutions to these equations are computationally expensive. An iterative linearising solution is presented.